Add support for streaming
#1
by
mariosasko
- opened
- README.md +212 -1
- ted_talks_iwslt.py +130 -92
README.md
CHANGED
@@ -145,6 +145,217 @@ configs:
|
|
145 |
- nl_hi_2014
|
146 |
- nl_hi_2015
|
147 |
- nl_hi_2016
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
148 |
---
|
149 |
|
150 |
# Dataset Card for Web Inventory of Transcribed & Translated(WIT) Ted Talks
|
@@ -470,4 +681,4 @@ cc-by-nc-nd-4.0
|
|
470 |
|
471 |
### Contributions
|
472 |
|
473 |
-
Thanks to [@skyprince999](https://github.com/skyprince999) for adding this dataset.
|
|
|
145 |
- nl_hi_2014
|
146 |
- nl_hi_2015
|
147 |
- nl_hi_2016
|
148 |
+
dataset_info:
|
149 |
+
- config_name: eu_ca_2014
|
150 |
+
features:
|
151 |
+
- name: translation
|
152 |
+
dtype:
|
153 |
+
translation:
|
154 |
+
languages:
|
155 |
+
- eu
|
156 |
+
- ca
|
157 |
+
splits:
|
158 |
+
- name: train
|
159 |
+
num_bytes: 15192
|
160 |
+
num_examples: 44
|
161 |
+
download_size: 1666674366
|
162 |
+
dataset_size: 15192
|
163 |
+
- config_name: eu_ca_2015
|
164 |
+
features:
|
165 |
+
- name: translation
|
166 |
+
dtype:
|
167 |
+
translation:
|
168 |
+
languages:
|
169 |
+
- eu
|
170 |
+
- ca
|
171 |
+
splits:
|
172 |
+
- name: train
|
173 |
+
num_bytes: 18768
|
174 |
+
num_examples: 52
|
175 |
+
download_size: 1666674366
|
176 |
+
dataset_size: 18768
|
177 |
+
- config_name: eu_ca_2016
|
178 |
+
features:
|
179 |
+
- name: translation
|
180 |
+
dtype:
|
181 |
+
translation:
|
182 |
+
languages:
|
183 |
+
- eu
|
184 |
+
- ca
|
185 |
+
splits:
|
186 |
+
- name: train
|
187 |
+
num_bytes: 19506
|
188 |
+
num_examples: 54
|
189 |
+
download_size: 1666674366
|
190 |
+
dataset_size: 19506
|
191 |
+
- config_name: nl_en_2014
|
192 |
+
features:
|
193 |
+
- name: translation
|
194 |
+
dtype:
|
195 |
+
translation:
|
196 |
+
languages:
|
197 |
+
- nl
|
198 |
+
- en
|
199 |
+
splits:
|
200 |
+
- name: train
|
201 |
+
num_bytes: 1035545
|
202 |
+
num_examples: 2966
|
203 |
+
download_size: 1666674366
|
204 |
+
dataset_size: 1035545
|
205 |
+
- config_name: nl_en_2015
|
206 |
+
features:
|
207 |
+
- name: translation
|
208 |
+
dtype:
|
209 |
+
translation:
|
210 |
+
languages:
|
211 |
+
- nl
|
212 |
+
- en
|
213 |
+
splits:
|
214 |
+
- name: train
|
215 |
+
num_bytes: 1292610
|
216 |
+
num_examples: 3550
|
217 |
+
download_size: 1666674366
|
218 |
+
dataset_size: 1292610
|
219 |
+
- config_name: nl_en_2016
|
220 |
+
features:
|
221 |
+
- name: translation
|
222 |
+
dtype:
|
223 |
+
translation:
|
224 |
+
languages:
|
225 |
+
- nl
|
226 |
+
- en
|
227 |
+
splits:
|
228 |
+
- name: train
|
229 |
+
num_bytes: 1434207
|
230 |
+
num_examples: 3852
|
231 |
+
download_size: 1666674366
|
232 |
+
dataset_size: 1434207
|
233 |
+
- config_name: nl_hi_2014
|
234 |
+
features:
|
235 |
+
- name: translation
|
236 |
+
dtype:
|
237 |
+
translation:
|
238 |
+
languages:
|
239 |
+
- nl
|
240 |
+
- hi
|
241 |
+
splits:
|
242 |
+
- name: train
|
243 |
+
num_bytes: 214870
|
244 |
+
num_examples: 367
|
245 |
+
download_size: 1666674366
|
246 |
+
dataset_size: 214870
|
247 |
+
- config_name: nl_hi_2015
|
248 |
+
features:
|
249 |
+
- name: translation
|
250 |
+
dtype:
|
251 |
+
translation:
|
252 |
+
languages:
|
253 |
+
- nl
|
254 |
+
- hi
|
255 |
+
splits:
|
256 |
+
- name: train
|
257 |
+
num_bytes: 252192
|
258 |
+
num_examples: 421
|
259 |
+
download_size: 1666674366
|
260 |
+
dataset_size: 252192
|
261 |
+
- config_name: nl_hi_2016
|
262 |
+
features:
|
263 |
+
- name: translation
|
264 |
+
dtype:
|
265 |
+
translation:
|
266 |
+
languages:
|
267 |
+
- nl
|
268 |
+
- hi
|
269 |
+
splits:
|
270 |
+
- name: train
|
271 |
+
num_bytes: 310922
|
272 |
+
num_examples: 496
|
273 |
+
download_size: 1666674366
|
274 |
+
dataset_size: 310922
|
275 |
+
- config_name: de_ja_2014
|
276 |
+
features:
|
277 |
+
- name: translation
|
278 |
+
dtype:
|
279 |
+
translation:
|
280 |
+
languages:
|
281 |
+
- de
|
282 |
+
- ja
|
283 |
+
splits:
|
284 |
+
- name: train
|
285 |
+
num_bytes: 1074403
|
286 |
+
num_examples: 2536
|
287 |
+
download_size: 1666674366
|
288 |
+
dataset_size: 1074403
|
289 |
+
- config_name: de_ja_2015
|
290 |
+
features:
|
291 |
+
- name: translation
|
292 |
+
dtype:
|
293 |
+
translation:
|
294 |
+
languages:
|
295 |
+
- de
|
296 |
+
- ja
|
297 |
+
splits:
|
298 |
+
- name: train
|
299 |
+
num_bytes: 1442047
|
300 |
+
num_examples: 3247
|
301 |
+
download_size: 1666674366
|
302 |
+
dataset_size: 1442047
|
303 |
+
- config_name: de_ja_2016
|
304 |
+
features:
|
305 |
+
- name: translation
|
306 |
+
dtype:
|
307 |
+
translation:
|
308 |
+
languages:
|
309 |
+
- de
|
310 |
+
- ja
|
311 |
+
splits:
|
312 |
+
- name: train
|
313 |
+
num_bytes: 1630729
|
314 |
+
num_examples: 3590
|
315 |
+
download_size: 1666674366
|
316 |
+
dataset_size: 1630729
|
317 |
+
- config_name: fr-ca_hi_2014
|
318 |
+
features:
|
319 |
+
- name: translation
|
320 |
+
dtype:
|
321 |
+
translation:
|
322 |
+
languages:
|
323 |
+
- fr-ca
|
324 |
+
- hi
|
325 |
+
splits:
|
326 |
+
- name: train
|
327 |
+
num_bytes: 74472
|
328 |
+
num_examples: 127
|
329 |
+
download_size: 1666674366
|
330 |
+
dataset_size: 74472
|
331 |
+
- config_name: fr-ca_hi_2015
|
332 |
+
features:
|
333 |
+
- name: translation
|
334 |
+
dtype:
|
335 |
+
translation:
|
336 |
+
languages:
|
337 |
+
- fr-ca
|
338 |
+
- hi
|
339 |
+
splits:
|
340 |
+
- name: train
|
341 |
+
num_bytes: 82448
|
342 |
+
num_examples: 141
|
343 |
+
download_size: 1666674366
|
344 |
+
dataset_size: 82448
|
345 |
+
- config_name: fr-ca_hi_2016
|
346 |
+
features:
|
347 |
+
- name: translation
|
348 |
+
dtype:
|
349 |
+
translation:
|
350 |
+
languages:
|
351 |
+
- fr-ca
|
352 |
+
- hi
|
353 |
+
splits:
|
354 |
+
- name: train
|
355 |
+
num_bytes: 93425
|
356 |
+
num_examples: 156
|
357 |
+
download_size: 1666674366
|
358 |
+
dataset_size: 93425
|
359 |
---
|
360 |
|
361 |
# Dataset Card for Web Inventory of Transcribed & Translated(WIT) Ted Talks
|
|
|
681 |
|
682 |
### Contributions
|
683 |
|
684 |
+
Thanks to [@skyprince999](https://github.com/skyprince999) for adding this dataset.
|
ted_talks_iwslt.py
CHANGED
@@ -15,14 +15,13 @@
|
|
15 |
"""TED TALKS IWSLT: Web Inventory of Transcribed and Translated Ted Talks in 109 languages."""
|
16 |
|
17 |
|
18 |
-
import
|
19 |
import xml.etree.ElementTree as ET
|
20 |
import zipfile
|
21 |
from collections import defaultdict
|
22 |
|
23 |
import datasets
|
24 |
|
25 |
-
|
26 |
logger = datasets.logging.get_logger(__name__)
|
27 |
|
28 |
|
@@ -63,7 +62,9 @@ _LICENSE = "CC-BY-NC-4.0"
|
|
63 |
# TODO: Add link to the official dataset URLs here
|
64 |
# The HuggingFace dataset library don't host the datasets but only point to the original files
|
65 |
# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
|
66 |
-
_URL =
|
|
|
|
|
67 |
|
68 |
_LANGUAGES = (
|
69 |
"mr",
|
@@ -189,7 +190,11 @@ _LANGUAGE_PAIRS = [
|
|
189 |
# Year subscripts for the specific folder
|
190 |
_YEAR = {"2014": "-20140120", "2015": "-20150530", "2016": "-20160408"}
|
191 |
|
192 |
-
_YEAR_FOLDER = {
|
|
|
|
|
|
|
|
|
193 |
|
194 |
|
195 |
class TedTalksIWSLTConfig(datasets.BuilderConfig):
|
@@ -209,10 +214,14 @@ class TedTalksIWSLTConfig(datasets.BuilderConfig):
|
|
209 |
source, target = language_pair
|
210 |
assert source in _LANGUAGES, f"Invalid source code in language pair: {source}"
|
211 |
assert target in _LANGUAGES, f"Invalid target code in language pair: {target}"
|
212 |
-
assert
|
|
|
|
|
213 |
assert year in _YEAR.keys()
|
214 |
|
215 |
-
description =
|
|
|
|
|
216 |
super(TedTalksIWSLTConfig, self).__init__(
|
217 |
name=name,
|
218 |
description=description,
|
@@ -232,7 +241,9 @@ class TedTalksIWSLT(datasets.GeneratorBasedBuilder):
|
|
232 |
BUILDER_CONFIG_CLASS = TedTalksIWSLTConfig
|
233 |
|
234 |
BUILDER_CONFIGS = [
|
235 |
-
TedTalksIWSLTConfig(
|
|
|
|
|
236 |
for language_pair in _LANGUAGE_PAIRS
|
237 |
for year in _YEAR.keys()
|
238 |
]
|
@@ -240,7 +251,9 @@ class TedTalksIWSLT(datasets.GeneratorBasedBuilder):
|
|
240 |
def _info(self):
|
241 |
features = datasets.Features(
|
242 |
{
|
243 |
-
"translation": datasets.features.Translation(
|
|
|
|
|
244 |
},
|
245 |
)
|
246 |
|
@@ -263,88 +276,79 @@ class TedTalksIWSLT(datasets.GeneratorBasedBuilder):
|
|
263 |
|
264 |
def _split_generators(self, dl_manager):
|
265 |
"""Returns SplitGenerators."""
|
266 |
-
|
267 |
-
# If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
|
268 |
-
|
269 |
-
# dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs
|
270 |
-
# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
|
271 |
-
# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
|
272 |
-
my_urls = _URL
|
273 |
-
language_pair = self.config.language_pair
|
274 |
-
year = self.config.year
|
275 |
-
|
276 |
-
data_dir = dl_manager.download_and_extract(my_urls)
|
277 |
-
|
278 |
-
zip_file_pair0 = os.path.join(data_dir, _YEAR_FOLDER[year] + "/ted_" + language_pair[0] + _YEAR[year] + ".zip")
|
279 |
-
zip_file_pair1 = os.path.join(data_dir, _YEAR_FOLDER[year] + "/ted_" + language_pair[1] + _YEAR[year] + ".zip")
|
280 |
|
281 |
return [
|
282 |
datasets.SplitGenerator(
|
283 |
name=datasets.Split.TRAIN,
|
284 |
-
# These kwargs will be passed to _generate_examples
|
285 |
gen_kwargs={
|
286 |
-
"
|
287 |
-
"split": "train",
|
288 |
},
|
289 |
),
|
290 |
]
|
291 |
|
292 |
-
def _generate_examples(self,
|
293 |
"""Yields examples."""
|
294 |
-
|
295 |
-
|
296 |
-
|
297 |
-
|
298 |
-
|
299 |
-
|
300 |
-
|
301 |
-
|
302 |
-
|
303 |
-
|
304 |
-
|
305 |
-
|
306 |
-
|
307 |
-
|
308 |
-
|
309 |
-
|
310 |
-
|
311 |
-
|
312 |
-
|
313 |
-
|
314 |
-
|
315 |
-
|
316 |
-
|
317 |
-
|
318 |
-
|
319 |
-
|
320 |
-
|
321 |
-
|
322 |
-
|
323 |
-
|
324 |
-
|
325 |
-
|
326 |
-
|
327 |
-
|
328 |
-
|
329 |
-
|
330 |
-
|
331 |
-
|
332 |
-
|
333 |
-
|
334 |
-
|
335 |
-
|
336 |
-
|
337 |
-
|
338 |
-
|
339 |
-
|
340 |
-
|
341 |
-
|
342 |
-
|
343 |
-
|
344 |
-
|
345 |
-
|
346 |
-
|
347 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
348 |
source_ids = list()
|
349 |
target_ids = list()
|
350 |
|
@@ -353,8 +357,18 @@ class TedTalksIWSLT(datasets.GeneratorBasedBuilder):
|
|
353 |
translation = list()
|
354 |
|
355 |
for talkid in comm_talkids:
|
356 |
-
source = list(
|
357 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
358 |
|
359 |
if len(source) == 0 or len(target) == 0:
|
360 |
pass
|
@@ -362,33 +376,57 @@ class TedTalksIWSLT(datasets.GeneratorBasedBuilder):
|
|
362 |
source = source[0]
|
363 |
target = target[0]
|
364 |
|
365 |
-
if source.get("head")[0].get("description") and target.get("head")[0].get(
|
366 |
-
|
|
|
|
|
|
|
|
|
|
|
367 |
temp_dict = dict()
|
368 |
temp_dict["id"] = source.get("head")[0].get("talkid")[0] + "_1"
|
369 |
temp_dict[language_pair[0]] = (
|
370 |
-
source.get("head")[0]
|
|
|
|
|
371 |
)
|
372 |
temp_dict[language_pair[1]] = (
|
373 |
-
target.get("head")[0]
|
|
|
|
|
374 |
)
|
375 |
translation.append(temp_dict)
|
376 |
|
377 |
-
if source.get("head")[0].get("title") and target.get("head")[0].get(
|
378 |
-
|
|
|
|
|
|
|
|
|
|
|
379 |
temp_dict = dict()
|
380 |
temp_dict["id"] = source.get("head")[0].get("talkid")[0] + "_2"
|
381 |
temp_dict[language_pair[0]] = source.get("head")[0].get("title")[0]
|
382 |
temp_dict[language_pair[1]] = target.get("head")[0].get("title")[0]
|
383 |
translation.append(temp_dict)
|
384 |
|
385 |
-
if source.get("head")[0].get("seekvideo") and target.get("head")[0].get(
|
386 |
-
|
387 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
388 |
|
389 |
transc = zip(source_transc, target_transc)
|
390 |
transcriptions = [
|
391 |
-
{
|
|
|
|
|
|
|
|
|
392 |
for s, t in transc
|
393 |
]
|
394 |
translation.extend(transcriptions)
|
|
|
15 |
"""TED TALKS IWSLT: Web Inventory of Transcribed and Translated Ted Talks in 109 languages."""
|
16 |
|
17 |
|
18 |
+
import io
|
19 |
import xml.etree.ElementTree as ET
|
20 |
import zipfile
|
21 |
from collections import defaultdict
|
22 |
|
23 |
import datasets
|
24 |
|
|
|
25 |
logger = datasets.logging.get_logger(__name__)
|
26 |
|
27 |
|
|
|
62 |
# TODO: Add link to the official dataset URLs here
|
63 |
# The HuggingFace dataset library don't host the datasets but only point to the original files
|
64 |
# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
|
65 |
+
_URL = (
|
66 |
+
"https://huggingface.co/datasets/ted_talks_iwslt/resolve/main/data/XML_releases.tgz"
|
67 |
+
)
|
68 |
|
69 |
_LANGUAGES = (
|
70 |
"mr",
|
|
|
190 |
# Year subscripts for the specific folder
|
191 |
_YEAR = {"2014": "-20140120", "2015": "-20150530", "2016": "-20160408"}
|
192 |
|
193 |
+
_YEAR_FOLDER = {
|
194 |
+
"2014": "XML_releases/xml-20140120",
|
195 |
+
"2015": "XML_releases/xml-20150616",
|
196 |
+
"2016": "XML_releases/xml",
|
197 |
+
}
|
198 |
|
199 |
|
200 |
class TedTalksIWSLTConfig(datasets.BuilderConfig):
|
|
|
214 |
source, target = language_pair
|
215 |
assert source in _LANGUAGES, f"Invalid source code in language pair: {source}"
|
216 |
assert target in _LANGUAGES, f"Invalid target code in language pair: {target}"
|
217 |
+
assert (
|
218 |
+
source != target
|
219 |
+
), f"Source::{source} and Target::{target} language pairs cannot be the same!"
|
220 |
assert year in _YEAR.keys()
|
221 |
|
222 |
+
description = (
|
223 |
+
f"Translation Ted Talks dataset (WIT3) between {source} and {target}"
|
224 |
+
)
|
225 |
super(TedTalksIWSLTConfig, self).__init__(
|
226 |
name=name,
|
227 |
description=description,
|
|
|
241 |
BUILDER_CONFIG_CLASS = TedTalksIWSLTConfig
|
242 |
|
243 |
BUILDER_CONFIGS = [
|
244 |
+
TedTalksIWSLTConfig(
|
245 |
+
language_pair=language_pair, year=year, version=datasets.Version("1.1.0")
|
246 |
+
)
|
247 |
for language_pair in _LANGUAGE_PAIRS
|
248 |
for year in _YEAR.keys()
|
249 |
]
|
|
|
251 |
def _info(self):
|
252 |
features = datasets.Features(
|
253 |
{
|
254 |
+
"translation": datasets.features.Translation(
|
255 |
+
languages=self.config.language_pair
|
256 |
+
),
|
257 |
},
|
258 |
)
|
259 |
|
|
|
276 |
|
277 |
def _split_generators(self, dl_manager):
|
278 |
"""Returns SplitGenerators."""
|
279 |
+
data_dir = dl_manager.download(_URL)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
280 |
|
281 |
return [
|
282 |
datasets.SplitGenerator(
|
283 |
name=datasets.Split.TRAIN,
|
|
|
284 |
gen_kwargs={
|
285 |
+
"files": dl_manager.iter_archive(data_dir),
|
|
|
286 |
},
|
287 |
),
|
288 |
]
|
289 |
|
290 |
+
def _generate_examples(self, files):
|
291 |
"""Yields examples."""
|
292 |
+
|
293 |
+
def parse_zip_file(path, file):
|
294 |
+
def et_to_dict(tree):
|
295 |
+
"""This is used to convert the xml to a list of dicts"""
|
296 |
+
|
297 |
+
dct = {tree.tag: {} if tree.attrib else None}
|
298 |
+
children = list(tree)
|
299 |
+
if children:
|
300 |
+
dd = defaultdict(list)
|
301 |
+
for dc in map(et_to_dict, children):
|
302 |
+
for k, v in dc.items():
|
303 |
+
dd[k].append(v)
|
304 |
+
dct = {tree.tag: dd}
|
305 |
+
if tree.attrib:
|
306 |
+
dct[tree.tag].update((k, v) for k, v in tree.attrib.items())
|
307 |
+
if tree.text:
|
308 |
+
text = tree.text.strip()
|
309 |
+
if children or tree.attrib:
|
310 |
+
if text:
|
311 |
+
dct[tree.tag]["text"] = text
|
312 |
+
else:
|
313 |
+
dct[tree.tag] = text
|
314 |
+
return dct
|
315 |
+
|
316 |
+
with zipfile.ZipFile(io.BytesIO(file)) as zf:
|
317 |
+
try:
|
318 |
+
tree = ET.parse(zf.open(path.split("/")[-1][:-3] + "xml"))
|
319 |
+
root = tree.getroot()
|
320 |
+
talks = et_to_dict(root).get("xml").get("file")
|
321 |
+
ids = [talk.get("head")[0].get("talkid") for talk in talks]
|
322 |
+
except Exception as pe:
|
323 |
+
logger.warning(f"ERROR: {pe}")
|
324 |
+
logger.warning(
|
325 |
+
"This likely means that you have a malformed XML file!"
|
326 |
+
)
|
327 |
+
ids = []
|
328 |
+
return talks, ids
|
329 |
+
|
330 |
+
language_pair = self.config.language_pair
|
331 |
+
year = self.config.year
|
332 |
+
|
333 |
+
source_file_path = (
|
334 |
+
_YEAR_FOLDER[year] + "/ted_" + language_pair[0] + _YEAR[year] + ".zip"
|
335 |
+
)
|
336 |
+
target_file_path = (
|
337 |
+
_YEAR_FOLDER[year] + "/ted_" + language_pair[1] + _YEAR[year] + ".zip"
|
338 |
+
)
|
339 |
+
|
340 |
+
source_talks, source_ids = None, None
|
341 |
+
target_talks, target_ids = None, None
|
342 |
+
for path, file in files:
|
343 |
+
if source_ids is not None and target_ids is not None:
|
344 |
+
break
|
345 |
+
|
346 |
+
if source_ids is None and path.endswith(source_file_path):
|
347 |
+
source_talks, source_ids = parse_zip_file(path, file.read())
|
348 |
+
elif target_ids is None and path.endswith(target_file_path):
|
349 |
+
target_talks, target_ids = parse_zip_file(path, file.read())
|
350 |
+
|
351 |
+
if source_ids is None or target_ids is None:
|
352 |
source_ids = list()
|
353 |
target_ids = list()
|
354 |
|
|
|
357 |
translation = list()
|
358 |
|
359 |
for talkid in comm_talkids:
|
360 |
+
source = list(
|
361 |
+
filter(
|
362 |
+
lambda talk: talk.get("head")[0].get("talkid") == talkid,
|
363 |
+
source_talks,
|
364 |
+
)
|
365 |
+
)
|
366 |
+
target = list(
|
367 |
+
filter(
|
368 |
+
lambda talk: talk.get("head")[0].get("talkid") == talkid,
|
369 |
+
target_talks,
|
370 |
+
)
|
371 |
+
)
|
372 |
|
373 |
if len(source) == 0 or len(target) == 0:
|
374 |
pass
|
|
|
376 |
source = source[0]
|
377 |
target = target[0]
|
378 |
|
379 |
+
if source.get("head")[0].get("description") and target.get("head")[0].get(
|
380 |
+
"description"
|
381 |
+
):
|
382 |
+
if (
|
383 |
+
source.get("head")[0].get("description")[0]
|
384 |
+
and target.get("head")[0].get("description")[0]
|
385 |
+
):
|
386 |
temp_dict = dict()
|
387 |
temp_dict["id"] = source.get("head")[0].get("talkid")[0] + "_1"
|
388 |
temp_dict[language_pair[0]] = (
|
389 |
+
source.get("head")[0]
|
390 |
+
.get("description")[0]
|
391 |
+
.replace("TED Talk Subtitles and Transcript: ", "")
|
392 |
)
|
393 |
temp_dict[language_pair[1]] = (
|
394 |
+
target.get("head")[0]
|
395 |
+
.get("description")[0]
|
396 |
+
.replace("TED Talk Subtitles and Transcript: ", "")
|
397 |
)
|
398 |
translation.append(temp_dict)
|
399 |
|
400 |
+
if source.get("head")[0].get("title") and target.get("head")[0].get(
|
401 |
+
"title"
|
402 |
+
):
|
403 |
+
if (
|
404 |
+
source.get("head")[0].get("title")[0]
|
405 |
+
and target.get("head")[0].get("title")[0]
|
406 |
+
):
|
407 |
temp_dict = dict()
|
408 |
temp_dict["id"] = source.get("head")[0].get("talkid")[0] + "_2"
|
409 |
temp_dict[language_pair[0]] = source.get("head")[0].get("title")[0]
|
410 |
temp_dict[language_pair[1]] = target.get("head")[0].get("title")[0]
|
411 |
translation.append(temp_dict)
|
412 |
|
413 |
+
if source.get("head")[0].get("seekvideo") and target.get("head")[0].get(
|
414 |
+
"seekvideo"
|
415 |
+
):
|
416 |
+
source_transc = (
|
417 |
+
source.get("head")[0].get("transcription")[0].get("seekvideo")
|
418 |
+
)
|
419 |
+
target_transc = (
|
420 |
+
target.get("head")[0].get("transcription")[0].get("seekvideo")
|
421 |
+
)
|
422 |
|
423 |
transc = zip(source_transc, target_transc)
|
424 |
transcriptions = [
|
425 |
+
{
|
426 |
+
"id": s.get("id"),
|
427 |
+
language_pair[0]: s.get("text"),
|
428 |
+
language_pair[1]: t.get("text"),
|
429 |
+
}
|
430 |
for s, t in transc
|
431 |
]
|
432 |
translation.extend(transcriptions)
|